An efficient approach for outlier detection with imperfect data labels

Mathematics

• Outlier Detection 100%
• Imperfect 84%
• Likelihood 25%
• Outlier 14%
• Learning 13%
• K-means Clustering 11%
• False Alarm Rate 10%
• kernel 10%
• Clustering Methods 10%
• Classifier 8%
• Inconsistent 8%
• Training 7%
• Trade-offs 7%
• Life 6%
• Experiment 5%
• Object 5%
• Model 4%
• Computing 4%
• Denote 4%
• Performance 4%
• Framework 4%
• Class 2%

Engineering & Materials Science

• Anomaly detection 77%
• Labels 63%
• Classifiers 6%
• Experiments 3%